[AISWorld] CFP: Big Multimedia Data and Applications in Frontiers in Big Data

[Mouzhi Ge]

Topic: Big Multimedia Data and Applications
Journal: Frontiers in Big Data

========
Web and submission
https://www.frontiersin.org/research-topics/49519/big-multimedia-data-and-applications

========
Manuscript Submission Deadline 
22 April 2023

========
Scope of the special issue
MultiMedia (MM) information, such as text, audio, images, video, animation, and
interactive data, allows fast and effective communication about people’ lives,
their behaviors, works, interests; additionally, they are also the digital
testimony of facts, objects, and locations. The widespread availability of
cheap media technologies (e.g., digital cameras and video cameras, smart
phones, etc.) dramatically increased the availability of MM data, their
production and utilization at cheap costs. In addition, the use of Online
Social Networks (OSNs) has caused at the same time MM data to be disseminated
and shared to a wide audience of people.

For all intents and purposes, this enormous amount of MM content generated at
unpredictable rates constitutes an instance of Big Data. Thus, modern Big Data
Analytics techniques can be used to support advanced analytics by solving the
volume, variety and velocity issues typical of such data, at the same time,
leveraging the related multimedia features.

The new challenges in the area of multimedia and big data have created
opportunities to explore the valuable information using big data analytics. In
order to drive the next horizon of multimedia research, big data solutions are
used to optimize processes, reduce decision-making time, and so on. Given the
complex nature of the multimedia, big data analytics for multimedia is demanded
to address the interaction and flexibility issues among the new intelligent
objects.

The number of possible applications that can benefit from the analysis of huge
amounts of multimedia data and the techniques (e.g., Computer Vision,
Machine/Deep Learning, etc.) already available for processing them (e.g.,
speech recognition, text understanding, image analysis, video processing, etc.)
is frightening: Social Network Analysis, Computer Assisted Diagnosis, Video
Surveillance, Cyber Security, Virtual Assistants, Smart Cities, just to cite
some of the most diffused.

As a result, the purpose of this Research Topic is to gather original research
articles from both academia and industry on Big Multimedia Data Analytics
applications. We welcome articles particularly focusing on the design and
application of data-driven analysis techniques that use large amounts of data
with the related multimedia features, eventually to solve a specific task
within the above listed domains, both for real-time and batch contexts. Review
articles discussing the current state of the art are also welcome.

========
Potential topics include but are not limited to the following:

• Large Scale Multimedia Search
• Automatic Tagging of Big Multimedia Data
• Big Multimedia Data Fusion
• Interactive Interfaces for Big Multimedia Data
• Big Multimedia Data Representation Learning
• Concept and event-based Multimedia Search in Large Collections
• Big Multimedia Data mining
• Multimedia Social Networks Analysis
• Misinformation Mining in Social Networks using Big Multimedia Data
• Medical Decision Support Applications using Large Multimodal Data
• Big Multimedia Data Analytics for Cyber Security Applications
• Big Multimedia Data Analytics for Virtual Assistants
• Big Multimedia Data Analytics for Smart Cities
• IoT and Multimedia Data Analytics
• Multimedia Analytics for Social Networks
• Machine Learning and Deep Learning for Multimedia Data Analytics 

========
Guest Editors
Vincenzo Moscato, University of Naples Federico II, Italy
Mouzhi Ge, Deggendorf Institute of Technology, Germany
Fabio Persia,  University of L'Aquila, Italy